Key Principles of Weak Consistency
- Trade-off between consistency and performance: Weak consistency sacrifices some level of data consistency to achieve better performance and scalability.
- Focus on eventual consistency: Updates are eventually meet across all nodes, but there’s no guarantee of immediate visibility.
- Client-centric approaches: Some models like “Read Your Own Writes” provide consistency guarantees for individual clients, even if global consistency is not achieved.
Weak Consistency in System Design
Weak consistency is a relaxed approach to data consistency in distributed systems. It doesn’t guarantee that all clients will see the same version of the data at the same time, or that updates will be reflected immediately across all nodes. This means there may be a temporary lag between a write operation and when the update is visible to all clients.
Important Topisc for Weak Consistency in System Design
- Importance of Weak Consistency in Systems
- Characteristics of Weak Consistency
- Key Principles of Weak Consistency
- Weak Consistency Comparison with Other Consistency Models
- Types of Weak Consistency Models
- Challenges with Weak Consistency
- Real-World Example of Weak Consistency
- Impact of weak consistency on system performance, scalability, and availability
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